Myung-Jin Choi

Catechin-capped gold nanoparticles: green synthesis, characterization, and catalytic activity toward 4-nitrophenol reduction.

An eco-friendly approach is described for the green synthesis of gold nanoparticles using catechin as a reducing and capping agent. The reaction occurred at room temperature within 1xa0h without the use of any external energy and an excellent yield (99%) was obtained, as determined by inductively coupled plasma mass spectrometry. Various shapes of gold nanoparticles with an estimated diameter of 16.6xa0nm were green-synthesized. Notably, the capping of freshly synthesized gold nanoparticles by catechin was clearly visualized with the aid of microscopic techniques, including high-resolution transmission electron microscopy, atomic force microscopy, and field emission scanning electron microscopy. Strong peaks in the X-ray diffraction pattern of the as-prepared gold nanoparticles confirmed their crystalline nature. The catalytic activity of the as-prepared gold nanoparticles was observed in the reduction of 4-nitrophenol to 4-aminophenol in the presence of NaBH4. The results suggest that the newly prepared gold nanoparticles have potential uses in catalysis.

Conjugate heat transfer and particle deposition in the modified chemical vapor deposition process: Effects of torch speed and solid layer

Abstract A study has been carried out for the conjugate heat transfer and particle deposition that occur during the modified chemical vapor deposition (MCVD) process. The analysis includes thermophoretic particle transport in the gas flow and heat transfer through the solid layer; the effects of variable properties in both the gas and the solid regions are included. A notable feature of the study is the inclusion of the effects of periodic heating due to the repeated traversing of the torch and the effects of the increasing solid layer thickness as the particles deposit. A new concept uses a two torch formulation to simulate the torch heating from both the present and the previous passes. This formulation is able to predict the minimum wall temperature in front of the torch, which is closely related to the deposition efficiency. Localized heating of the moving torch is studied using the heat flux boundary condition on the tube wall. The calculated surface temperature distribution and the deposition efficiency are in good agreement with experimental data. Of particular interest are the effects of torch speed and solid layer thickness on the efficiency, the rate of deposition of the particles and the taper length.

Earthworm extracts utilized in the green synthesis of gold nanoparticles capable of reinforcing the anticoagulant activities of heparin.

Gold nanoparticles were obtained using a green synthesis approach with aqueous earthworm extracts without any additional reducing or capping agents. The gold nanoparticles were characterized using UV-visible spectrophotometry, high-resolution transmission electron microscopy, atomic force microscopy, field emission scanning electron microscopy, X-ray diffraction, Fourier transform infrared spectroscopy, and inductively coupled plasma mass spectrometry. The anticoagulant activity of the gold nanoparticles was assessed using the activated partial thromboplastin time and was mildly enhanced by combining the gold nanoparticles with heparin. In addition to the generation of spherical nanoparticles with an average diameter of 6.13u2009±u20092.13xa0nm, cubic and block-shaped nanoparticles with an average aspect ratio, defined as the length divided by width, of 1.47 were also observed.

Sampling-Based RBDO of Ship Hull Structures Considering Thermo-Elasto-Plastic Residual Deformation

We present a shape optimization method using a sampling-based RBDO method linked with a commercial finite element analysis (FEA) code ANSYS, which is applicable to residual deformation problems of the ship hull structure in welding process. The programming language ANSYS Parametric Design Language (APDL) and shell elements are used for the thermo-elasto-plastic analysis. The shape of the ship hull structure is modeled using the bicubic Ferguson patch and coordinate components of vertices, tangential vectors of boundary curves are selected as design variables. The sensitivity of probabilistic constraint is calculated from the probabilistic sensitivity analysis using the score function and Monte Carlo Simulation (MCS) on the surrogate model constructed by using the Dynamic Kriging (DKG) method. The sequential quadratic programming (SQP) algorithm is used for the optimization. In two numerical examples, the suggested optimization method is applied to practical residual deformation problems in welding ship hull structures, which proves the sampling-based RBDO can be successfully utilized for obtaining a reliable optimum design in highly nonlinear multi-physics problem of thermo-elasto-plasticity.

Shape-design optimization of hull structures considering thermal deformation

We developed a shape-design optimization method for the thermo-elastoplasticity problems that are applicable to the welding or thermal deformation of hull structures. The point is to determine the shape-design parameters such that the deformed shape after welding fits very well to a desired design. The geometric parameters of curved surfaces are selected as the design parameters. The shell finite elements, forward finite difference sensitivity, modified method of feasible direction algorithm and a programming language ANSYS Parametric Design Language in the established code ANSYS are employed in the shape optimization. The objective function is the weighted summation of differences between the deformed and the target geometries. The proposed method is effective even though new design variables are added to the design space during the optimization process since the multiple steps of design optimization are used during the whole optimization process. To obtain the better optimal design, the weights are determined for the next design optimization, based on the previous optimal results. Numerical examples demonstrate that the localized severe deviations from the target design are effectively prevented in the optimal design.

Upcycling of jellyfish (Nemopilema nomurai) sea wastes as highly valuable reducing agents for green synthesis of gold nanoparticles and their antitumor and anti-inflammatory activity

Abstract Due to its tentacle poison and huge body, giant jellyfish (Nemopilema nomurai) poses challenging issues to the environment and ecosystems. Here we developed, upcycling a giant jellyfish extract as a reducing agent, a green synthetic method of gold nanoparticles (JF-AuNPs) which possess biological activities. The colloidal solutions of JF-AuNPs were blue, violet, purple and pink depending on the extract concentration. UV-visible spectra exhibited two surface plasmon resonance bands at 5 4 0u2009∼u2009550u2009nm and 810u2009nm. Spherical shapes with an average size of 35.2u2009±u20098.7u2009nm and triangular nanoplates with an average height of 70.5u2009±u200930.3u2009nm were observed. A face-centered cubic structure was confirmed by high-resolution X-ray diffraction. JF-AuNPs exhibited significant cytotoxic effect against HeLa cancer cells but not against normal cells such as NIH-3T3 and Raw 264.7 cells. In HeLa cells, JF-AuNPs decreased the phosphorylation of AKT and ERK, which are crucial for cell proliferation. Also, JF-AuNPs decreased NO secretion and iNOS expression levels, resulting in anti-inflammatory effects in LPS-inflamed macrophages. Collectively, we established a green synthesis of anti-tumorigenic and anti-inflammatory JF-AuNPs using the extract of jellyfish sea wastes. Thus, beneficial effects of JF-AgNPs must be weighed in further studies in vivo and it can be potent nanomedicine for future applications.

Experimental Validation of Isogeometric Optimal Design

Abstract In this paper, the CAD data for the optimal shape design obtained by isogeometric shape optimization is directly used to fabricate the specimen by using 3D printer for the experimental validation. In a conventional finite element method, the geometric approximation inherent in the mesh leads to the accuracy issue in response analysis and design sensitivity analysis. Furthermore, in the finite element based shape optimization, subsequent communication with CAD description is required in the design optimization process, which results in the loss of optimal design information during the communication. Isogeometric analysis method employs the same NURBS basis functions and control points used in CAD systems, which enables to use exact geometrical properties like normal vector and curvature information in the response analysis and design sensitivity analysis procedure. Also, it vastly simplify the design modification of complex geometries without communicating with the CAD description of geometry during design optimization process. Therefore, the information of optimal design and material volume is exactly reflected to fabricate the specimen for experimental validation. Through the design optimization examples of elasticity problem, it is experimentally shown that the optimal design has higher stiffness than the initial design. Also, the experimental results match very well with the numerical results. Using a non-contact optical 3D deformation measuring system for strain distribution, it is shown that the stress concentration is significantly alleviated in the optimal design compared with the initial design.